Currently, virtualization is an important topic in the IT (Information Technology) industry. The promise of virtualization is the ability to manage multiple computing devices (e.g., servers) in order to optimize a certain metric. The most common metric is server utilization, i.e., workload is arranged in such a way that the CPU (central processing unit) is not in contention for resources and is able to achieve maximum throughput. For this kind of optimization, the locations of the servers are not important.
A new metric to optimize is the power consumption. There are two reasons: (1) rising cost of energy; and (2) new servers such as computer blades consume over 30 kilowatts (kW) of power per rack. This power consumption exceeds the limit of the local power grid in many existing data centers.
To save energy, non-peak workload could be consolidated into a smaller number of servers and idle servers could be powered down. On the other hand, to satisfy the power constraint, workload could be spread over several servers to keep the power and thermal demands (power capping) within the capacity of the facility. These two important optimizations can only be done if the physical locations of the servers are known. This is not the case today. Large data centers can have hundreds to thousands of servers, installed at different times and made by different vendors. There is no way to automatically determine the locations of these servers.
During the installation phase, usually it is the facility engineer who decides where to locate the equipment based on the power and thermal requirements. After that, the system administrator generates a logical name for the machine. Each machine can have one or many logical names depending on the application. From then on, the system management software only deals with the machine names and it does not know about their physical locations. That is why, in many existing data centers, the exact location of each server is not known.
Accordingly, techniques are needed for identifying locations of equipment in such data centers.